Integrations · AWS
Industrial data into AWS, without a bespoke pipeline.
Connect the equipment once, name the tags once, and deliver to AWS IoT Core as a configured target, instead of maintaining an export script nobody owns.
- Direction
- Outbound from the plant to AWS IoT Core
- Delivered
- Each reading as JSON: device name and ID, tag name, value, data type and the time it was read
- Reliability
- Local buffering with replay on reconnect
- Control
- You choose which devices send to AWS; a pipeline can send single tags
Data path
What actually moves, and where it stops.
Initiated from inside the plant, buffered when the link drops
Field
- PLCs, CNCs, robots
- OPC UA servers
- Meters and SCADA
Proxus
- Collect at the line
- Model into the namespace
- Buffer and forward
AWS
- MQTT topic
- IoT rules
- downstream services
How it works
From the machine to AWS, in four steps.
- 01
Connect the assets
Native drivers collect from controllers, machines and OPC UA servers on site.
- 02
Give signals names
Tags get names and scaling at the point of collection, so AWS receives names rather than register addresses.
- 03
Publish to AWS
An outbound target publishes the readings of the devices attached to it to an AWS IoT Core topic over MQTT, port 8883.
- 04
Keep the plant copy
The same data stays in the historian on the hub you host, so line-side use does not depend on the cloud link.
What you get
Why teams route AWS through Proxus.
-
Plant stays in control
You choose which devices send to AWS, and can change that without touching collection.
-
Renewed certificates, no edits
The gateway reads the thing’s certificate from the Certificate Store at every send, so a renewed or replaced certificate is used without changing the target.
-
Your topic, your IoT rules
Readings are published to the topic you set (proxus_device_data by default), so AWS IoT rules route them onward from one place.
-
Checked from the sending gateway
Test Connection connects with the thing’s certificate from the gateway you choose, so a wrong endpoint or certificate shows before any data is sent.
Where it is used
Typical deployments.
-
Multi-site data lake ingestion
A consistent stream from every plant, with names attached before it arrives.
-
Cloud analytics and dashboards
Feed cloud-native tooling while operations keeps its own live views.
-
Remote monitoring of distributed assets
Field sites report to a central AWS account without opening inbound access.
- Targets
- AWS IoT Core over MQTT on port 8883; REST endpoints and brokers reachable from the plant are also supported
- Payload
- One JSON message per reading: deviceId, deviceName, measureName, timestamp, measureValueType and the value
- Strategies
- Pass Through, On Change, or Pipelines Only (only what a pipeline sends)
- Security
- The thing’s X.509 device certificate from the Proxus Certificate Store; the endpoint is verified against Amazon Root CA 1
- You configure
- EndPoint, ClientId, CertificateThumbprint, Topic. Test Connection checks the address and credentials from the hub or from a gateway you choose, without writing data.
Proven in production
Running in production at these plants.
-
Manufacturing
Digital factory data management
MEXT Digital Factory
Read the case study -
Mining & energy
Mining, fleet and solar on one platform
Kaltun Mining
Ask us about this deployment -
Energy
Grid monitoring at the edge
CK Enerji
Ask us about this deployment -
Manufacturing
Unified Namespace with Oracle ERP
Pilenpak
Ask us about this deployment
Questions
Before you wire it up.
- Which AWS service does Proxus deliver to?
- AWS IoT Core is the direct target. From there, data can move into whatever storage and analytics services your account uses.
- Can several plants publish into one AWS account?
- Yes, and they publish the same modelled structure, which is what keeps cloud-side processing written once rather than per site.
- How is authentication handled?
- With the thing’s X.509 device certificate from the Proxus Certificate Store; the endpoint is verified against Amazon Root CA 1. A renewed certificate is picked up without editing the target.
- Is there a way to limit volume?
- On-change delivery and filtering at the source both reduce what is published, without reducing what you keep in your own historian.
Other integrations
- Cloud
Microsoft Azure Send plant data to Azure IoT Hub, or write it in batches to Azure Data Lake Storage Gen2. Microsoft Azure integration
- Streaming and events
MQTT & Sparkplug B Subscribe to the namespace on each gateway’s built-in broker, publish to your own broker, and collect from devices that publish their own values. MQTT & Sparkplug B integration
- Database
InfluxDB Stream industrial time-series readings into InfluxDB 2.x. InfluxDB integration
Next step
See it delivering into your own AWS.
Bring one machine and an AWS IoT Core thing with its certificate. We connect the machine, publish to your topic in front of you, and show what the gateway does while the link is down.
- 01
Scoping call
Equipment, protocols, sites and the systems the data has to reach.
- 02
Technical walkthrough
A working demo against a scenario that resembles your plant, not a generic tour.
- 03
Pilot plan
A defined first line or site, with the deployment and security questions answered up front.
- 04
Roll-out
The same templates bring the next lines and sites online.